code: def _rank_correlation(
      y_obs: np.ndarray, y_pred: np.ndarray, se_pred: np.ndarray
  ) -> float:
      with np.errstate(invalid="ignore"):
          rho, _ = spearmanr(y_pred, y_obs)
      return float(rho)
  
file_path: Ax/ax/utils/stats/model_fit_stats.py
imports: from typing import Dict, Mapping, Optional, Protocol
  import numpy
  from scipy.stats import fisher_exact, norm, pearsonr, spearmanr
label_desc: Use image node_id 11 for calling a global function with example usage: _rank_correlation(y_obs, y_pred, se_pred) and returns: float